Dynamically partitioning processing across plurality of heterogeneous processors

ABSTRACT

A program is into at least two object files: one object file for each of the supported processor environments. During compilation, code characteristics, such as data locality, computational intensity, and data parallelism, are analyzed and recorded in the object file. During run time, the code characteristics are combined with runtime considerations, such as the current load on the processors and the size of the data being processed, to arrive at an overall value. The overall value is then used to determine which of the processors will be assigned the task. The values are assigned based on the characteristics of the various processors. For example, if one processor is better at handling intensive computations against large streams of data, programs that are highly computationally intensive and process large quantities of data are weighted in favor of that processor. The corresponding object is then loaded and executed on the assigned processor.

Related Applications

This application is a Continuation in Part of U.S. Patent Application US2002/0138637 A1 (09/816,004) filed Mar. 22, 2001 now U.S. Pat. 7,233,998titled “Computer Architecture and Software Cells for BroadbandNetworks,” and has at least one of the same inventors as the abovereferenced U.S. Patent Applications.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates in general to a system and method forpartitioning processing across heterogeneous processors. Moreparticularly, the present invention relates to a system and methodselecting one of the heterogeneous processors to run an object basedupon computational and load considerations.

2. Description of the Related Art

Computer systems are becoming more and more complex. The computerindustry typically doubles the performance of a computer system every 18months (i.e. personal computer, PDA, gaming console). In order for thecomputer industry to accomplish this task, the semiconductor industryproduces integrated circuits that double in performance every 18 months.A computer system uses integrated circuits for particular functionsbased upon the integrated circuits' architecture. Two fundamentalarchitectures are 1) microprocessor-based and 2) digital signalprocessor-based.

An integrated circuit with a microprocessor-based architecture istypically used to handle control operations whereas an integratedcircuit with a digital signal processor-based architecture is typicallydesigned to handle signal-processing manipulations (i.e. mathematicaloperations). As technology evolves, the computer industry and thesemiconductor industry realized the importance of using botharchitectures, or processor types, in a computer system design.

Software is another element in a computer system that has been evolvingalongside integrated circuit evolution. A software developer writes codein a manner that corresponds to the processor type that executes thecode. For example, a processor has a particular number of registers anda particular number of arithmetic logic units (ALUs) whereby thesoftware developer designs code to most effectively use the registersand the ALUs. In addition, the compiler used by the software developeris traditionally designed to compile code to operate on a specificprocessor environment. This traditionally limits the developer'sfunction to operate on a single environment. At runtime, the compiledcode is loaded and executed by the processor.

As the semiconductor industry incorporates multiple processor types ontoa single device, a challenge found for the software developer is towrite code based upon a multiple processor type architecture. A softwaredeveloper's code includes a plurality of subtasks whereby each subtaskmay be designed to run on a particular processor type. For example, asubtask that manages “control” operations is better suited to run on amicroprocessor.

However, there are many subtasks that run adequately on either processortype. In this case, the subtask would be best run on a processor that isnot heavily loaded at a particular time. A challenge found, however, isthat existing art requires a software developer to identify a processortype at compilation, not at runtime. A notable exception to this,however, is an environment that uses a “virtual machine” (such as aJava™Virtual Machine (JVM™), so that the applications are compiled tooperate using the virtual machine with each supported operatingenvironment employing a different version of the virtual machine thatoperates on the operating environment. A challenge of virtual machines,however, is that they require system resources to manage the virtualenvironment (i.e., a garbage-collected heap, etc.) and, because theapplication code is being performed by a virtual machine rather thandirectly by a processor, virtual machine code is traditionally slowerand less efficient than code that executes directly on a processor.

What is needed, therefore, is a system and method to compile source codeinto a plurality of object files adapted to execute on a plurality ofprocessor operating environments. What is further needed is a system andmethod that selects the object file to execute based upon currentcomputer system operational considerations.

SUMMARY

A system and method are provided to partition a computational problembased upon available processing resources in a heterogeneous processingenvironment and suitability to task. SPUs are faster processors that canprocess large amounts of data very quickly, while PUs have a richerinstruction set but are less efficient at processing a large amount ofdata. The breaking of the problem can be performed dynamically at runtime or can be performed statically (i.e., chosen by the programmer whenwriting the application). Both processors share a common memory map andboth processors can fetch virtual addresses and can fetch data from thecache. In addition, both the SPU and PU go through the same memoryaddress translation.

A software developer compiles a program into at least two objectfiles—one object file for each of the supported processor environments.During compilation, code characteristics, such as data locality,computational intensity, and data parallelism, are analyzed and recordedin the object file. During run time, the code characteristics arecombined with runtime considerations, such as the current load on theprocessors and the size of the data being processed, to arrive at anoverall value. The overall value is then used to determine which of theprocessors will be assigned the task. The values are assigned based onthe characteristics of the various processors. For example, if oneprocessor is better at handling intensive computations against largestreams of data, programs that are highly computationally intensive andprocess large quantities of data are weighted in favor of thatprocessor. The corresponding object is then loaded and executed on theassigned processor.

The foregoing is a summary and thus contains, by necessity,simplifications, generalizations, and omissions of detail; consequently,those skilled in the art will appreciate that the summary isillustrative only and is not intended to be in any way limiting. Otheraspects, inventive features, and advantages of the present invention, asdefined solely by the claims, will become apparent in the non-limitingdetailed description set forth below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may be better understood, and its numerousobjects, features, and advantages made apparent to those skilled in theart by referencing the accompanying drawings. The use of the samereference symbols in different drawings indicates similar or identicalitems.

FIG. 1 illustrates—the overall architecture of a computer network inaccordance with the present invention;

FIG. 2 is a diagram illustrating the structure of a processing unit (PU)in accordance with the present invention;

FIG. 3 is a diagram illustrating the structure of a broadband engine(BE) in accordance with the present invention;

FIG. 4 is a diagram illustrating the structure of an synergisticprocessing unit (SPU) in accordance with the present invention;

FIG. 5 is a diagram illustrating the structure of a processing unit,visualizer (VS) and an optical interface in accordance with the presentinvention;

FIG. 6 is a diagram illustrating one combination of processing units inaccordance with the present invention;

FIG. 7 illustrates another combination of processing units in accordancewith the present invention;

FIG. 8 illustrates yet another combination of processing units inaccordance with the present invention;

FIG. 9 illustrates yet another combination of processing units inaccordance with the present invention;

FIG. 10 illustrates yet another combination of processing units inaccordance with the present invention;

FIG. 11A illustrates the integration of optical interfaces within a chippackage in accordance with the present invention;

FIG. 11B is a diagram of one configuration of processors using theoptical interfaces of FIG. 11A;

FIG. 11C is a diagram of another configuration of processors using theoptical interfaces of FIG. 11A;

FIG. 12A illustrates the structure of a memory system in accordance withthe present invention;

FIG. 12B illustrates the writing of data from a first broadband engineto a second broadband engine in accordance with the present invention;

FIG. 13 is a diagram of the structure of a shared memory for aprocessing unit in accordance with the present invention;

FIG. 14A illustrates one structure for a bank of the memory shown inFIG. 13;

FIG. 14B illustrates another structure for a bank of the memory shown inFIG. 13;

FIG. 15 illustrates a structure for a direct memory access controller inaccordance with the present invention;

FIG. 16 illustrates an alternative structure for a direct memory accesscontroller in accordance with the present invention;

FIGS. 17-31 illustrate the operation of data synchronization inaccordance with the present invention;

FIG. 32 is a three-state memory diagram illustrating the various statesof a memory location in accordance with the data synchronization schemeof the-present invention;

FIG. 33 illustrates the structure of a key control table for a hardwaresandbox in accordance with the present invention;

FIG. 34 illustrates a scheme for storing memory access keys for ahardware sandbox in accordance with the present invention;

FIG. 35 illustrates the structure of a memory access control table for ahardware sandbox in accordance with the present invention;

FIG. 36 is a flow diagram of the steps for accessing a memory sandboxusing the key control table of FIG. 33 and the memory access controltable of FIG. 35;

FIG. 37 illustrates the structure of a software cell in accordance withthe present invention;

FIG. 38 is a flow diagram of the steps for issuing remote procedurecalls to SPUs in accordance with the present invention;

FIG. 39 illustrates the structure of a dedicated pipeline for processingstreaming data in accordance with the present invention;

FIG. 40 is a flow diagram of the steps performed by the dedicatedpipeline of FIG. 39 in the processing of streaming data in accordancewith the present invention;

FIG. 41 illustrates an alternative structure for a dedicated pipelinefor the processing of streaming data in accordance with the presentinvention;

FIG. 42 illustrates a scheme for an absolute timer for coordinating theparallel processing of applications and data by SPUs in accordance withthe present invention;

FIG. 43 is a flowchart showing the steps taken to compile a given sourcecode into object files adapted to execute in a heterogeneous processorenvironment;

FIG. 44 is a flowchart showing steps taken by a loader in theheterogeneous processor environment selecting in selecting one of theheterogeneous processor types to execute an object file;

FIG. 45 is a flowchart showing steps taken by the loader in theheterogeneous processor environment identifying a preferred processorfor a given task;

FIG. 46 is a flowchart showing steps taken by an SPU processor inexecuting an object file scheduled to it by the loader; and

FIG. 47 is a block diagram illustrating a processing element having amain processor and a plurality of secondary processors sharing a systemmemory.

DETAILED DESCRIPTION

The following is intended to provide a detailed description of anexample of the invention and should not be taken to be limiting of theinvention itself. Rather, any number of variations may fall within thescope of the invention which is defined in the claims following thedescription.

The overall architecture for a computer system 101 in accordance withthe present invention is shown in FIG. 1.

As illustrated in this figure, system 101 includes network 104 to whichis connected a plurality of computers and computing devices. Network 104can be a LAN, a global network, such as the Internet, or any othercomputer network.

The computers and computing devices connected to network 104 (thenetwork's “members”) include, e.g., client computers 106, servercomputers 108, personal digital assistants (PDAs) 110, digitaltelevision (DTV) 112 and other wired or wireless computers and computingdevices. The processors employed by the members of network 104 areconstructed from the same common computing module. These processors alsopreferably all have the same ISA and perform processing in accordancewith the same instruction set. The number of modules included within anyparticular processor depends upon the processing power required by thatprocessor.

For example, since servers 108 of system 101 perform more processing ofdata and applications than clients 106, servers 108 contain morecomputing modules than clients 106. PDAs 110, on the other hand, performthe least amount of processing. PDAs 110, therefore, contain thesmallest number of computing modules. DTV 112 performs a level ofprocessing between that of clients 106 and servers 108. DTV 112,therefore, contains a number of computing modules between that ofclients 106 and servers 108. As discussed below, each computing modulecontains a processing controller and a plurality of identical processingunits for performing parallel processing of the data and applicationstransmitted over network 104.

This homogeneous configuration for system 101 facilitates adaptability,processing speed and processing efficiency. Because each member ofsystem 101 performs processing using one or more (or some fraction) ofthe same computing module, the particular computer or computing deviceperforming the actual processing of data and applications isunimportant. The processing of a particular application and data,moreover, can be shared among the network's members. By uniquelyidentifying the cells comprising the data and applications processed bysystem 101 throughout the system, the processing results can betransmitted to the computer or computing device requesting theprocessing regardless of where this processing occurred. Because themodules performing this processing have a common structure and employ acommon ISA, the computational burdens of an added layer of software toachieve compatibility among the processors is avoided. This architectureand programming model facilitates the processing speed necessary toexecute, e.g., real-time, multimedia applications. To take furtheradvantage of the processing speeds and efficiencies facilitated bysystem 101, the data and applications processed by this system arepackaged into uniquely identified, uniformly formatted software cells102. Each software cell 102 contains, or can contain, both applicationsand data. Each software cell also contains an ID to globally identifythe cell throughout network 104 and system 101. This uniformity ofstructure for the software cells, and the software cells' uniqueidentification throughout the network, facilitates the processing ofapplications and data on any computer or computing device of thenetwork. For example, a client 106 may formulate a software cell 102but, because of the limited processing capabilities of client 106,transmit this software cell to a server 108 for processing. Softwarecells can migrate, therefore, throughout network 104 for processing onthe basis of the availability of processing resources on the network.

The homogeneous structure of processors and software cells of system 101also avoids many of the problems of today's heterogeneous networks. Forexample, inefficient programming models which seek to permit processingof applications on any ISA using any instruction set, e.g., virtualmachines such as the Java virtual machine, are avoided. System 101,therefore, can implement broadband processing far more effectively andefficiently than today's networks.

The basic processing module for all members of network 104 is theprocessing unit (PU). FIG. 2 illustrates the structure of a PU. As shownin this figure, PE 201 comprises a processing unit (PU) 203, a directmemory access controller (DMAC) 205 and a plurality of synergisticprocessing units (SPUs), namely, SPU 207, SPU 209, SPU 211, SPU 213, SPU215, SPU 217, SPU 219 and SPU 221. A local PE bus 223 transmits data andapplications among the SPUs, DMAC 205 and PU 203. Local PE bus 223 canhave, e.g., a conventional architecture or be implemented as a packetswitch network. Implementation as a packet switch network, whilerequiring more hardware, increases available bandwidth.

PE 201 can be constructed using various methods for implementing digitallogic. PE 201 preferably is constructed, however, as a single integratedcircuit employing a complementary metal oxide semiconductor (CMOS) on asilicon substrate. Alternative materials for substrates include galliumarsinide, gallium aluminum arsinide and other so-called III-B compoundsemploying a wide variety of dopants. PE 201 also could be implementedusing superconducting material, e.g., rapid single-flux-quantum (RSFQ)logic.

PE 201 is closely associated with a dynamic random access memory (DRAM)225 through a high bandwidth memory connection 227. DRAM 225 functionsas the main memory for PE 201. Although a DRAM 225 preferably is adynamic random access memory, DRAM 225 could be implemented using othermeans, e.g., as a static random access memory (SRAM), a magnetic randomaccess memory (MRAM), an optical memory or a holographic memory. DMAC205 facilitates the transfer of data between DRAM 225 and the SPUs andPU of PE 201. As further discussed below, DMAC 205 designates for eachSPU an exclusive area in DRAM 225 into which only the SPU can write dataand from which only the SPU can read data. This exclusive area isdesignated a “sandbox.”

PU 203 can be, e.g., a standard processor capable of stand-aloneprocessing of data and applications. In operation, PU 203 schedules andorchestrates the processing of data and applications by the SPUs. TheSPUs preferably are single instruction, multiple data (SIMD) processors.Under the control of PU 203, the SPUs perform the processing of thesedata and applications in a parallel and independent manner. DMAC 205controls accesses by PU 203 and the SPUs to the data and applicationsstored in the shared DRAM 225. Although PE 201 preferably includes eightSPUs, a greater or lesser number of SPUs can be employed in a PUdepending upon the processing power required. Also, a number of PUs,such as PE 201, may be joined or packaged together to provide enhancedprocessing power.

For example, as shown in FIG. 3, four PUs may be packaged or joinedtogether, e.g., within one or more chip packages, to form a singleprocessor for a member of network 104. This configuration is designateda broadband engine (BE). As shown in FIG. 3, BE 301 contains four PUs,namely, PE 303, PE 305, PE 307 and PE 309. Communications among thesePUs are over BE bus 311. Broad bandwidth memory connection 313 providescommunication between shared DRAM 315 and these PUs. In lieu of BE bus311, communications among the PUs of BE 301 can occur through DRAM 315and this memory connection.

Input/output (I/O) interface 317 and external bus 319 providecommunications between broadband engine 301 and the other members ofnetwork 104. Each PU of BE 301 performs processing of data andapplications in a parallel and independent manner analogous to theparallel and independent processing of applications and data performedby the SPUs of a PU.

FIG. 4 illustrates the structure of an SPU. SPU 402 includes localmemory 406, registers 410, four floating point units 412 and fourinteger units 414. Again, however, depending upon the processing powerrequired, a greater or lesser number of floating points units 412 andinteger units 414 can be employed. In a preferred embodiment, localmemory 406 contains 128 kilobytes of storage, and the capacity ofregisters 410 is 128.times.128 bits. Floating point units 412 preferablyoperate at a speed of 32 billion floating point operations per second(32 GFLOPS), and integer units 414 preferably operate at a speed of 32billion operations per second (32 GOPS).

Local memory 406 is not a cache memory. Local memory 406 is preferablyconstructed as an SRAM. Cache coherency support for an SPU isunnecessary. A PU may require cache coherency support for direct memoryaccesses initiated by the PU. Cache coherency support is not required,however, for direct memory accesses initiated by an SPU or for accessesfrom and to external devices.

SPU 402 further includes bus 404 for transmitting applications and datato and from the SPU. In a preferred embodiment, this bus is 1,024 bitswide. SPU 402 further includes internal busses 408, 420 and 418. In apreferred embodiment, bus 408 has a width of 256 bits and providescommunications between local memory 406 and registers 410. Busses 420and 418 provide communications between, respectively, registers 410 andfloating point units 412, and registers 410 and integer units 414. In apreferred embodiment, the width of busses 418 and 420 from registers 410to the floating point or integer units is 384 bits, and the width ofbusses 418 and 420 from the floating point or integer units to registers410 is 128 bits. The larger width of these busses from registers 410 tothe floating point or integer units than from these units to registers410 accommodates the larger data flow from registers 410 duringprocessing. A maximum of three words are needed for each calculation.The result of each calculation, however, normally is only one word.

FIGS. 5-10 further illustrate the modular structure of the processors ofthe members of network 104. For example, as shown in FIG. 5, a processormay comprise a single PU 502. As discussed above, this PU typicallycomprises a PU, DMAC and eight SPUs. Each SPU includes local storage(LS). On the other hand, a processor may comprise the structure ofvisualizer (VS) 505. As shown in FIG. 5, VS 505 comprises PU 512, DMAC514 and four SPUs, namely, SPU 516, SPU 518, SPU 520 and SPU 522. Thespace within the chip package normally occupied by the other four SPUsof a PU is occupied in this case by pixel engine 508, image cache 510and cathode ray tube controller (CRTC) 504. Depending upon the speed ofcommunications required for PU 502 or VS 505, optical interface 506 alsomay be included on the chip package.

Using this standardized, modular structure, numerous other variations ofprocessors can be constructed easily and efficiently. For example, theprocessor shown in FIG. 6 comprises two chip packages, namely, chippackage 602 comprising a BE and chip package 604 comprising four VSs.Input/output (I/O) 606 provides an interface between the BE of chippackage 602 and network 104. Bus 608 provides communications betweenchip package 602 and chip package 604. Input output processor (IOP) 610controls the flow of data into and out of I/O 606. I/O 606 may befabricated as an application specific integrated circuit (ASIC). Theoutput from the VSs is video signal 612.

FIG. 7 illustrates a chip package for a BE 702 with two opticalinterfaces 704 and 706 for providing ultra high speed communications tothe other members of network 104 (or other chip packages locallyconnected). BE 702 can function as, e.g., a server on network 104.

The chip package of FIG. 8 comprises two PEs 802 and 804 and two VSs 806and 808. An I/O 810 provides an interface between the chip package andnetwork 104. The output from the chip package is a video signal. Thisconfiguration may function as, e.g., a graphics work station.

FIG. 9 illustrates yet another configuration. This configurationcontains one-half of the processing power of the configurationillustrated in FIG. 8. Instead of two PUs, one PE 902 is provided, andinstead of two VSs, one VS 904 is provided. I/O 906 has one-half thebandwidth of the I/O illustrated in FIG. 8. Such a processor also mayfunction, however, as a graphics work station.

A final configuration is shown in FIG. 10. This processor consists ofonly a single VS 1002 and an I/O 1004. This configuration may functionas, e.g., a PDA.

FIG. 11A illustrates the integration of optical interfaces into a chippackage of a processor of network 104. These optical interfaces convertoptical signals to electrical signals and electrical signals to opticalsignals and can be constructed from a variety of materials including,e.g., gallium arsinide, aluminum gallium arsinide, germanium and otherelements or compounds. As shown in this figure, optical interfaces 1104and 1106 are fabricated on the chip package of BE 1102. BE bus 1108provides communication among the PUs of BE 1102, namely, PE 1110, PE1112, PE 1114, PE 1116, and these optical interfaces. Optical interface1104 includes two ports, namely, port 1118 and port 1120, and opticalinterface 1106 also includes two ports, namely, port 1122 and port 1124.Ports 1118, 1120, 1122 and 1124 are connected to, respectively, opticalwave guides 1126, 1128, 1130 and 1132. Optical signals are transmittedto and from BE 1102 through these optical wave guides via the ports ofoptical interfaces 1104 and 1106 plurality of BEs can be connectedtogether in various configurations using such optical wave guides andthe four optical ports of each BE. For example, as shown in FIG. 11B,two or more BEs, e.g., BE 1152, BE 1154 and BE 1156, can be connectedserially through such optical ports. In this example, optical interface1166 of BE 1152 is connected through its optical ports to the opticalports of optical interface 1160 of BE 1154. In a similar manner, theoptical ports of optical interface 1162 on BE 1154 are connected to theoptical ports of optical interface 1164 of BE 1156.

A matrix configuration is illustrated in FIG. 11C. In thisconfiguration, the optical interface of each BE is connected to twoother BEs. As shown in this figure, one of the optical ports of opticalinterface 1188 of BE 1172 is connected to an optical port of opticalinterface 1182 of BE 1176. The other optical port of optical interface1188 is connected to an optical port of optical interface 1184 of BE1178. In a similar manner, one optical port of optical interface 1190 ofBE 1174 is connected to the other optical port of optical interface 1184of BE 1178. The other optical port of optical interface 1190 isconnected to an optical port of optical interface 1186 of BE 1180. Thismatrix configuration can be extended in a similar manner to other BEs.

Using either a serial configuration or a matrix configuration, aprocessor for network 104 can be constructed of any desired size andpower. Of course, additional ports can be added to the opticalinterfaces of the BEs, or to processors having a greater or lessernumber of PUs than a BE, to form other configurations.

FIG. 12A illustrates the control system and structure for the DRAM of aBE. A similar control system and structure is employed in processorshaving other sizes and containing more or less PUs. As shown in thisfigure, a cross-bar switch connects each DMAC 1210 of the four PUscomprising BE 1201 to eight bank controls 1206. Each bank control 1206controls eight banks 1208 (only four are shown in the figure) of DRAM1204. DRAM 1204, therefore, comprises a total of sixty-four banks. In apreferred embodiment, DRAM 1204 has a capacity of 64 megabytes, and eachbank has a capacity of 1 megabyte. The smallest addressable unit withineach bank, in this preferred embodiment, is a block of 1024 bits.

BE 1201 also includes switch unit 1212. Switch unit 1212 enables otherSPUs on BEs closely coupled to BE 1201 to access DRAM 1204. A second BE,therefore, can be closely coupled to a first BE, and each SPU of each BEcan address twice the number of memory locations normally accessible toan SPU. The direct reading or writing of data from or to the DRAM of afirst BE from or to the DRAM of a second BE can occur through a switchunit such as switch unit 1212.

For example, as shown in FIG. 12B, to accomplish such writing, the SPUof a first BE, e.g., SPU 1220 of BE 1222, issues a write command to amemory location of a DRAM of a second BE, e.g., DRAM 1228 of BE 1226(rather than, as in the usual case, to DRAM 1224 of BE 1222). DMAC 1230of BE 1222 sends the write command through cross-bar switch 1221 to bankcontrol 1234, and bank control 1234 transmits the command to an externalport 1232 connected to bank control 1234. DMAC 1238 of BE 1226 receivesthe write command and transfers this command to switch unit 1240 of BE1226. Switch unit 1240 identifies the DRAM address contained in thewrite command and sends the data for storage in this address throughbank control 1242 of BE 1226 to bank 1244 of DRAM 1228. Switch unit1240, therefore, enables both DRAM 1224 and DRAM 1228 to function as asingle memory space for the SPUs of BE 1226.

FIG. 13 shows the configuration of the sixty-four banks of a DRAM. Thesebanks are arranged into eight rows, namely, rows 1302, 1304, 1306, 1308,1310, 1312, 1314 and 1316 and eight columns, namely, columns 1320, 1322,1324, 1326, 1328, 1330, 1332 and 1334. Each row is controlled by a bankcontroller. Each bank controller, therefore, controls eight megabytes ofmemory.

FIGS. 14A and 14B illustrate different configurations for storing andaccessing the smallest addressable memory unit of a DRAM, e.g., a blockof 1024 bits. In FIG. 14A, DMAC 1402 stores in a single bank 1404 eight1024 bit blocks 1406. In FIG. 14B, on the other hand, while DMAC 1412reads and writes blocks of data containing 1024 bits, these blocks areinterleaved between two banks, namely, bank 1414 and bank 1416. Each ofthese banks, therefore, contains sixteen blocks of data, and each blockof data contains 512 bits. This interleaving can facilitate fasteraccessing of the DRAM and is useful in the processing of certainapplications.

FIG. 15 illustrates the architecture for a DMAC 1504 within a PE. Asillustrated in this figure, the structural hardware comprising DMAC 1506is distributed throughout the PE such that each SPU 1502 has directaccess to a structural node 1504 of DMAC 1506. Each node executes thelogic appropriate for memory accesses by the SPU to which the node hasdirect access.

FIG. 16 shows an alternative embodiment of the DMAC, namely, anon-distributed architecture. In this case, the structural hardware ofDMAC 1606 is centralized. SPUs 1602 and PU 1604 communicate with DMAC1606 via local PE bus 1607. DMAC 1606 is connected through a cross-barswitch to a bus 1608. Bus 1608 is connected to DRAM 1610.

As discussed above, all of the multiple SPUs of a PU can independentlyaccess data in the shared DRAM. As a result, a first SPU could beoperating upon particular data in its local storage at a time duringwhich a second SPU requests these data. If the data were provided to thesecond SPU at that time from the shared DRAM, the data could be invalidbecause of the first SPU's ongoing processing which could change thedata's value. If the second processor received the data from the sharedDRAM at that time, therefore, the second processor could generate anerroneous result. For example, the data could be a specific value for aglobal variable. If the first processor changed that value during itsprocessing, the second processor would receive an outdated value. Ascheme is necessary, therefore, to synchronize the SPUs' reading andwriting of data from and to memory locations within the shared DRAM.This scheme must prevent the reading of data from a memory location uponwhich another SPU currently is operating in its local storage and,therefore, which are not current, and the writing of data into a memorylocation storing current data.

To overcome these problems, for each addressable memory location of theDRAM, an additional segment of memory is allocated in the DRAM forstoring status information relating to the data stored in the memorylocation. This status information includes a full/empty (F/E) bit, theidentification of an SPU (SPU ID) requesting data from the memorylocation and the address of the SPU's local storage (LS address) towhich the requested data should be read. An addressable memory locationof the DRAM can be of any size. In a preferred embodiment, this size is1024 bits.

The setting of the F/E bit to 1 indicates that the data stored in theassociated memory location are current. The setting of the F/E bit to 0,on the other hand, indicates that the data stored in the associatedmemory location are not current. If an SPU requests the data when thisbit is set to 0, the SPU is prevented from immediately reading the data.In this case, an SPU ID identifying the SPU requesting the data, and anLS address identifying the memory location within the local storage ofthis SPU to which the data are to be read when the data become current,are entered into the additional memory segment.

An additional memory segment also is allocated for each memory locationwithin the local storage of the SPUs. This additional memory segmentstores one bit, designated the “busy bit.” The busy bit is used toreserve the associated LS memory location for the storage of specificdata to be retrieved from the DRAM. If the busy bit is set to 1 for aparticular memory location in local storage, the SPU can use this memorylocation only for the writing of these specific data. On the other hand,if the busy bit is set to 0 for a particular memory location in localstorage, the SPU can use this memory location for the writing of anydata.

Examples of the manner in which the F/E bit, the SPU ID, the LS addressand the busy bit are used to synchronize the reading and writing of datafrom and to the shared DRAM of a PU are illustrated in FIGS. 17-31.

As shown in FIG. 17, one or more PUs, e.g., PE 1720, interact with DRAM1702. PE 1720 includes SPU 1722 and SPU 1740. SPU 1722 includes controllogic 1724, and SPU 1740 includes control logic 1742. SPU 1722 alsoincludes local storage 1726. This local storage includes a plurality ofaddressable memory locations 1728. SPU 1740 includes local storage 1744,and this local storage also includes a plurality of addressable memorylocations 1746. All of these addressable memory locations preferably are1024 bits in size.

An additional segment of memory is associated with each LS addressablememory location. For example, memory segments 1729 and 1734 areassociated with, respectively, local memory locations 1731 and 1732, andmemory segment 1752 is associated with local memory location 1750. A“busy bit,” as discussed above, is stored in each of these additionalmemory segments. Local memory location 1732 is shown with several Xs toindicate that this location contains data.

DRAM 1702 contains a plurality of addressable memory locations 1704,including memory locations 1706 and 1708. These memory locationspreferably also are 1024 bits in size. An additional segment of memoryalso is associated with each of these memory locations. For example,additional memory segment 1760 is associated with memory location 1706,and additional memory segment 1762 is associated with memory location1708. Status information relating to the data stored in each memorylocation is stored in the memory segment associated with the memorylocation. This status information includes, as discussed above, the F/Ebit, the SPU ID and the LS address. For example, for memory location1708, this status information includes F/E bit 1712, SPU ID 1714 and LSaddress 1716.

Using the status information and the busy bit, the synchronized readingand writing of data from and to the shared DRAM among the SPUs of a PU,or a group of PUs, can be achieved.

FIG. 18 illustrates the initiation of the synchronized writing of datafrom LS memory location 1732 of SPU 1722 to memory location 1708 of DRAM1702. Control 1724 of SPU 1722 initiates the synchronized writing ofthese data. Since memory location 1708 is empty, F/E bit 1712 is set to0. As a result, the data in LS location 1732 can be written into memorylocation 1708. If this bit were set to 1 to indicate that memorylocation 1708 is full and contains current, valid data, on the otherhand, control 1722 would receive an error message and be prohibited fromwriting data into this memory location.

The result of the successful synchronized writing of the data intomemory location 1708 is shown in FIG. 19. The written data are stored inmemory location 1708, and F/E bit 1712 is set to 1. This settingindicates that memory location 1708 is full and that the data in thismemory location are current and valid.

FIG. 20 illustrates the initiation of the synchronized reading of datafrom memory location 1708 of DRAM 1702 to LS memory location 1750 oflocal storage 1744. To initiate this reading, the busy bit in memorysegment 1752 of LS memory location 1750 is set to 1 to reserve thismemory location for these data. The setting of this busy bit to 1prevents SPU 1740 from storing other data in this memory location.

As shown in FIG. 21, control logic 1742 next issues a synchronize readcommand for memory location 1708 of DRAM 1702. Since F/E bit 1712associated with this memory location is set to 1, the data stored inmemory location 1708 are considered current and valid. As a result, inpreparation for transferring the data from memory location 1708 to LSmemory location 1750, F/E bit 1712 is set to 0. This setting is shown inFIG. 22. The setting of this bit to 0 indicates that, following thereading of these data, the data in memory location 1708 will be invalid.

As shown in FIG. 23, the data within memory location 1708 next are readfrom memory location 1708 to LS memory location 1750. FIG. 24 shows thefinal state. A copy of the data in memory location 1708 is stored in LSmemory location 1750. F/E bit 1712 is set to 0 to indicate that the datain memory location 1708 are invalid. This invalidity is the result ofalterations to these data to be made by SPU 1740. The busy bit in memorysegment 1752 also is set to 0. This setting indicates that LS memorylocation 1750 now is available to SPU 1740 for any purpose, i.e., thisLS memory location no longer is in a reserved state waiting for thereceipt of specific data. LS memory location 1750, therefore, now can beaccessed by SPU 1740 for any purpose.

FIGS. 25-31 illustrate the synchronized reading of data from a memorylocation of DRAM 1702, e.g., memory location 1708, to an LS memorylocation of an SPU's local storage, e.g., LS memory location 1752 oflocal storage 1744, when the F/E bit for the memory location of DRAM1702 is set to 0 to indicate that the data in this memory location arenot current or valid. As shown in FIG. 25, to initiate this transfer,the busy bit in memory segment 1752 of LS memory location 1750 is set to1 to reserve this LS memory location for this transfer of data. As shownin FIG. 26, control logic 1742 next issues a synchronize read commandfor memory location 1708 of DRAM 1702. Since the F/E bit associated withthis memory location, F/E bit 1712, is set to 0, the data stored inmemory location 1708 are invalid. As a result, a signal is transmittedto control logic 1742 to block the immediate reading of data from thismemory location.

As shown in FIG. 27, the SPU ID 1714 and LS address 1716 for this readcommand next are written into memory segment 1762. In this case, the SPUID for SPU 1740 and the LS memory location for LS memory location 1750are written into memory segment 1762. When the data within memorylocation 1708 become current, therefore, this SPU ID and LS memorylocation are used for determining the location to which the current dataare to be transmitted.

The data in memory location 1708 become valid and current when an SPUwrites data into this memory location. The synchronized writing of datainto memory location 1708 from, e.g., memory location 1732 of SPU 1722,is illustrated in FIG. 28. This synchronized writing of these data ispermitted because F/E bit 1712 for this memory location is set to 0.

As shown in FIG. 29, following this writing, the data in memory location1708 become current and valid. SPU ID 1714 and LS address 1716 frommemory segment 1762, therefore, immediately are read from memory segment1762, and this information then is deleted from this segment. F/E bit1712 also is set to 0 in anticipation of the immediate reading of thedata in memory location 1708. As shown in FIG. 30, upon reading SPU ID1714 and LS address 1716, this information immediately is used forreading the valid data in memory location 1708 to LS memory location1750 of SPU 1740. The final state is shown in FIG. 31. This figure showsthe valid data from memory location 1708 copied to memory location 1750,the busy bit in memory segment 1752 set to 0 and F/E bit 1712 in memorysegment 1762 set to 0. The setting of this busy bit to 0 enables LSmemory location 1750 now to be accessed by SPU 1740 for any purpose. Thesetting of this F/E bit to 0 indicates that the data in memory location1708 no longer are current and valid.

FIG. 32 summarizes the operations described above and the various statesof a memory location of the DRAM based upon the states of the F/E bit,the SPU ID and the LS address stored in the memory segment correspondingto the memory location. The memory location can have three states. Thesethree states are an empty state 3280 in which the F/E bit is set to 0and no information is provided for the SPU ID or the LS address, a fullstate 3282 in which the F/E bit is set to 1 and no information isprovided for the SPU ID or LS address and a blocking state 3284 in whichthe F/E bit is set to 0 and information is provided for the SPU ID andLS address.

As shown in this figure, in empty state 3280, a synchronized writingoperation is permitted and results in a transition to full state 3282. Asynchronized reading operation, however, results in a transition to theblocking state 3284 because the data in the memory location, when thememory location is in the empty state, are not current.

In full state 3282, a synchronized reading operation is permitted andresults in a transition to empty state 3280. On the other hand, asynchronized writing operation in full state 3282 is prohibited toprevent overwriting of valid data. If such a writing operation isattempted in this state, no state change occurs and an error message istransmitted to the SPU's corresponding control logic.

In blocking state 3284, the synchronized writing of data into the memorylocation is permitted and results in a transition to empty state 3280.On the other hand, a synchronized reading operation in blocking state3284 is prohibited to prevent a conflict with the earlier synchronizedreading operation which resulted in this state. If a synchronizedreading operation is attempted in blocking state 3284, no state changeoccurs and an error message is transmitted to the SPU's correspondingcontrol logic.

The scheme described above for the synchronized reading and writing ofdata from and to the shared DRAM also can be used for eliminating thecomputational resources normally dedicated by a processor for readingdata from, and writing data to, external devices. This input/output(I/O) function could be performed by a PU. However, using a modificationof this synchronization scheme, an SPU running an appropriate programcan perform this function. For example, using this scheme, a PUreceiving an interrupt request for the transmission of data from an I/Ointerface initiated by an external device can delegate the handling ofthis request to this SPU. The SPU then issues a synchronize writecommand to the I/O interface. This interface in turn signals theexternal device that data now can be written into the DRAM. The SPU nextissues a synchronize read command to the DRAM to set the DRAM's relevantmemory space into a blocking state. The SPU also sets to 1 the busy bitsfor the memory locations of the SPU's local storage needed to receivethe data. In the blocking state, the additional memory segmentsassociated with the DRAM's relevant memory space contain the SPU's IDand the address of the relevant memory locations of the SPU's localstorage. The external device next issues a synchronize write command towrite the data directly to the DRAM's relevant memory space. Since thismemory space is in the blocking state, the data are immediately read outof this space into the memory locations of the SPU's local storageidentified in the additional memory segments. The busy bits for thesememory locations then are set to 0. When the external device completeswriting of the data, the SPU issues a signal to the PU that thetransmission is complete.

Using this scheme, therefore, data transfers from external devices canbe processed with minimal computational load on the PU. The SPUdelegated this function, however, should be able to issue an interruptrequest to the PU, and the external device should have direct access tothe DRAM.

The DRAM of each PU includes a plurality of “sandboxes.” A sandboxdefines an area of the shared DRAM beyond which a particular SPU, or setof SPUs, cannot read or write data. These sandboxes provide securityagainst the corruption of data being processed by one SPU by data beingprocessed by another SPU. These sandboxes also permit the downloading ofsoftware cells from network 104 into a particular sandbox without thepossibility of the software cell corrupting data throughout the DRAM. Inthe present invention, the sandboxes are implemented in the hardware ofthe DRAMs and DMACs. By implementing these sandboxes in this hardwarerather than in software, advantages in speed and security are obtained.

The PU of a PU controls the sandboxes assigned to the SPUs. Since the PUnormally operates only trusted programs, such as an operating system,this scheme does not jeopardize security. In accordance with thisscheme, the PU builds and maintains a key control table. This keycontrol table is illustrated in FIG. 33. As shown in this figure, eachentry in key control table 3302 contains an identification (ID) 3304 foran SPU, an SPU key 3306 for that SPU and a key mask 3308. The use ofthis key mask is explained below. Key control table 3302 preferably isstored in a relatively fast memory, such as a static random accessmemory (SRAM), and is associated with the DMAC. The entries in keycontrol table 3302 are controlled by the PU. When an SPU requests thewriting of data to, or the reading of data from, a particular storagelocation of the DRAM, the DMAC evaluates the SPU key 3306 assigned tothat SPU in key control table 3302 against a memory access keyassociated with that storage location.

As shown in FIG. 34, a dedicated memory segment 3410 is assigned to eachaddressable storage location 3406 of a DRAM 3402. A memory access key3412 for the storage location is stored in this dedicated memorysegment. As discussed above, a further additional dedicated memorysegment 3408, also associated with each addressable storage location3406, stores synchronization information for writing data to, andreading data from, the storage-location.

In operation, an SPU issues a DMA command to the DMAC. This commandincludes the address of a storage location 3406 of DRAM 3402. Beforeexecuting this command, the DMAC looks up the requesting SPU's key 3306in key control table 3302 using the SPU's ID 3304. The DMAC thencompares the SPU key 3306 of the requesting SPU to the memory access key3412 stored in the dedicated memory segment 3410 associated with thestorage location of the DRAM to which the SPU seeks access. If the twokeys do not match, the DMA command is not executed. On the other hand,if the two keys match, the DMA command proceeds and the requested memoryaccess is executed.

An alternative embodiment is illustrated in FIG. 35. In this embodiment,the PU also maintains a memory access control table 3502. Memory accesscontrol table 3502 contains an entry for each sandbox within the DRAM.In the particular example of FIG. 35, the DRAM contains 64 sandboxes.Each entry in memory access control table 3502 contains anidentification (ID) 3504 for a sandbox, a base memory address 3506, asandbox size 3508, a memory access key 3510 and an access key mask 3512.Base memory address 3506 provides the address in the DRAM which starts aparticular memory sandbox. Sandbox size 3508 provides the size of thesandbox and, therefore, the endpoint of the particular sandbox.

FIG. 36 is a flow diagram of the steps for executing a DMA command usingkey control table 3302 and memory access control table 3502. In step3602, an SPU issues a DMA command to the DMAC for access to a particularmemory location or locations within a sandbox. This command includes asandbox ID 3504 identifying the particular sandbox for which access isrequested. In step 3604, the DMAC looks up the requesting SPU's key 3306in key control table 3302 using the SPU's ID 3304. In step 3606, theDMAC uses the sandbox ID 3504 in the command to look up in memory accesscontrol table 3502 the memory access key 3510 associated with thatsandbox. In step 3608, the DMAC compares the SPU key 3306 assigned tothe requesting SPU to the access key 3510 associated with the sandbox.In step 3610, a determination is made of whether the two keys match. Ifthe two keys do not match, the process moves to step 3612 where the DMAcommand does not proceed and an error message is sent to either therequesting SPU, the PU or both. On the other hand, if at step 3610 thetwo keys are found to match, the process proceeds to step 3614 where theDMAC executes the DMA command.

The key masks for the SPU keys and the memory access keys providegreater flexibility to this system. A key mask for a key converts amasked bit into a wildcard. For example, if the key mask 3308 associatedwith an SPU key 3306 has its last two bits set to “mask,” designated by,e.g., setting these bits in key mask 3308 to 1, the SPU key can beeither a 1 or a 0 and still match the memory access key. For example,the SPU key might be 1010. This SPU key normally allows access only to asandbox having an access key of 1010. If the SPU key mask for this SPUkey is set to 0001, however, then this SPU key can be used to gainaccess to sandboxes having an access key of either 1010 or 1011.Similarly, an access key 1010 with a mask set to 0001 can be accessed byan SPU with an SPU key of either 1010 or 1011. Since both the SPU keymask and the memory key mask can be used simultaneously, numerousvariations of accessibility by the SPUs to the sandboxes can beestablished.

The present invention also provides a new programming model for theprocessors of system 101. This programming model employs software cells102. These cells can be transmitted to any processor on network 104 forprocessing. This new programming model also utilizes the unique modulararchitecture of system 101 and the processors of system 101.

Software cells are processed directly by the SPUs from the SPU's localstorage. The SPUs do not directly operate on any data or programs in theDRAM. Data and programs in the DRAM are read into the SPU's localstorage before the SPU processes these data and programs. The SPU'slocal storage, therefore, includes a program counter, stack and othersoftware elements for executing these programs. The PU controls the SPUsby issuing direct memory access (DMA) commands to the DMAC.

The structure of software cells 102 is illustrated in FIG. 37. As shownin this figure, a software cell, e.g., software cell 3702, containsrouting information section 3704 and body 3706. The informationcontained in routing information section 3704 is dependent upon theprotocol of network 104. Routing information section 3704 containsheader 3708, destination ID 3710, source ID 3712 and reply ID 3714. Thedestination ID includes a network address. Under the TCP/IP protocol,e.g., the network address is an Internet protocol (IP).address.Destination ID 3710 further includes the identity of the PU and SPU towhich the cell should be transmitted for processing. Source ID 3712contains a network address and identifies the PU and SPU from which thecell originated to enable the destination PU and SPU to obtainadditional information regarding the cell if necessary. Reply ID 3714contains a network address and identifies the PU and SPU to whichqueries regarding the cell, and the result of processing of the cell,should be directed.

Cell body 3706 contains information independent of the network'sprotocol. The exploded portion of FIG. 37 shows the details of cell body3706. Header 3720 of cell body 3706 identifies the start of the cellbody. Cell interface 3722 contains information necessary for the cell'sutilization. This information includes global unique ID 3724, requiredSPUs 3726, sandbox size 3728 and previous cell ID 3730.

Global unique ID 3724 uniquely identifies software cell 3702 throughoutnetwork 104. Global unique ID 3724 is generated on the basis of sourceID 3712, e.g. the unique identification of a PU or SPU within source ID3712, and the time and date of generation or transmission of softwarecell 3702. Required SPUs 3726 provides the minimum number of SPUsrequired to execute the cell. Sandbox size 3728 provides the amount ofprotected memory in the required SPUs' associated DRAM necessary toexecute the cell. Previous cell ID 3730 provides the identity of aprevious cell in a group of cells requiring sequential execution, e.g.,streaming data.

Implementation section 3732 contains the cell's core information. Thisinformation includes DMA command list 3734, programs 3736 and data 3738.Programs 3736 contain the programs to be run by the SPUs (called“spulets”), e.g., SPU programs 3760 and 3762, and data 3738 contain thedata to be processed with these programs. DMA command list 3734 containsa series of DMA commands needed to start the programs. These DMAcommands include DMA commands 3740, 3750, 3755 and 3758. The PU issuesthese DMA commands to the DMAC.

DMA command 3740 includes VID 3742. VID 3742 is the virtual ID of an SPUwhich is mapped to a physical ID when the DMA commands are issued. DMAcommand 3740 also includes load command 3744 and address 3746. Loadcommand 3744 directs the SPU to read particular information from theDRAM into local storage. Address 3746 provides the virtual address inthe DRAM containing this information. The information can be, e.g.,programs from programs section 3736, data from data section 3738 orother data. Finally, DMA command 3740 includes local storage address3748. This address identifies the address in local storage where theinformation should be loaded. DMA commands 3750 contain similarinformation. Other DMA commands are also possible.

DMA command list 3734 also includes a series of kick commands, e.g.,kick commands 3755 and 3758. Kick commands are commands issued by a PUto an SPU to initiate the processing of a cell. DMA kick command 3755includes virtual SPU ID 3752, kick command 3754 and program counter3756. Virtual SPU ID 3752 identifies the SPU to be kicked, kick command3754 provides the relevant kick command and program counter 3756provides the address for the program counter for executing the program.DMA kick command 3758 provides similar information for the same SPU oranother SPU.

As noted, the PUs treat the SPUs as independent processors, notco-processors. To control processing by the SPUs, therefore, the PU usescommands analogous to remote procedure calls. These commands aredesignated “SPU Remote Procedure Calls” (SRPCs). A PU implements an SRPCby issuing a series of DMA commands to the DMAC. The DMAC loads the SPUprogram and its associated stack frame into the local storage of an SPU.The PU then issues an initial kick to the SPU to execute the SPUProgram.

FIG. 38 illustrates the steps of an SRPC for executing an spulet. Thesteps performed by the PU in initiating processing of the spulet by adesignated SPU are shown in the first portion 3802 of FIG. 38, and thesteps performed by the designated SPU in processing the spulet are shownin the second portion 3804 of FIG. 38.

In step 3810, the PU evaluates the spulet and then designates an SPU forprocessing the spulet. In step 3812, the PU allocates space in the DRAMfor executing the spulet by issuing a DMA command to the DMAC to setmemory access keys for the necessary sandbox or sandboxes. In step 3814,the PU enables an interrupt request for the designated SPU to signalcompletion of the spulet. In step 3818, the PU issues a DMA command tothe DMAC to load the spulet from the DRAM to the local storage of theSPU. In step 3820, the DMA command is executed, and the spulet is readfrom the DRAM to the SPU's local storage. In step 3822, the PU issues aDMA command to the DMAC to load the stack frame associated with thespulet from the DRAM to the SPU's local storage. In step 3823, the DMAcommand is executed, and the stack frame is read from the DRAM to theSPU's local storage. In step 3824, the PU issues a DMA command for theDMAC to assign a key to the SPU to allow the SPU to read and write datafrom and to the hardware sandbox or sandboxes designated in step 3812.In step 3826, the DMAC updates the key control table (KTAB) with the keyassigned to the SPU. In step 3828, the PU issues a DMA command “kick” tothe SPU to start processing of the program. Other DMA commands may beissued by the PU in the execution of a particular SRPC depending uponthe particular spulet.

As indicated above, second portion 3804 of FIG. 38 illustrates the stepsperformed by the SPU in executing the spulet. In step 3830, the SPUbegins to execute the spulet in response to the kick command issued atstep 3828. In step 3832, the SPU, at the direction of the spulet,evaluates the spulet's associated stack frame. In step 3834, the SPUissues multiple DMA commands to the DMAC to load data designated asneeded by the stack frame from the DRAM to the SPU's local storage. Instep 3836, these DMA commands are executed, and the data are read fromthe DRAM to the SPU's local storage. In step 3838, the SPU executes thespulet and generates a result. In step 3840, the SPU issues a DMAcommand to the DMAC to store the result in the DRAM. In step 3842, theDMA command is executed and the result of the spulet is written from theSPU's local storage to the DRAM. In step 3844, the SPU issues aninterrupt request to the PU to signal that the SRPC has been completed.

The ability of SPUs to perform tasks independently under the directionof a PU enables a PU to dedicate a group of SPUs, and the memoryresources associated with a group of SPUs, to performing extended tasks.For example, a PU can dedicate one or more SPUs, and a group of memorysandboxes associated with these one or more SPUs, to receiving datatransmitted over network 104 over an extended period and to directingthe data received during this period to one or more other SPUs and theirassociated memory sandboxes for further processing. This ability isparticularly advantageous to processing streaming data transmitted overnetwork 104, e.g., streaming MPEG or streaming ATRAC audio or videodata. A PU can dedicate one or more SPUs and their associated memorysandboxes to receiving these data and one or more other SPUs and theirassociated memory sandboxes to decompressing and further processingthese data. In other words, the PU can establish a dedicated pipelinerelationship among a group of SPUs and their associated memory sandboxesfor processing such data.

In order for such processing to be performed efficiently, however, thepipeline's dedicated SPUs and memory sandboxes should remain dedicatedto the pipeline during periods in which processing of spulets comprisingthe data stream does not occur. In other words, the dedicated SPUs andtheir associated sandboxes should be placed in a reserved state duringthese periods. The reservation of an SPU and its associated memorysandbox or sandboxes upon completion of processing of an spulet iscalled a “resident termination.” A resident termination occurs inresponse to an instruction from a PU.

FIGS. 39, 40A and 40B illustrate the establishment of a dedicatedpipeline structure comprising a group of SPUs and their associatedsandboxes for the processing of streaming data, e.g., streaming MPEGdata. As shown in FIG. 39, the components of this pipeline structureinclude PE 3902 and DRAM 3918. PE 3902 includes PU 3904, DMAC 3906 and aplurality of SPUs, including SPU 3908, SPU 3910 and SPU 3912.Communications among PU 3904, DMAC 3906 and these SPUs occur through PEbus 3914. Wide bandwidth bus 3916 connects DMAC 3906 to DRAM 3918. DRAM3918 includes a plurality of sandboxes, e.g., sandbox 3920, sandbox3922, sandbox 3924 and sandbox 3926.

FIG. 40A illustrates the steps for establishing the dedicated pipeline.In step 4010, PU 3904 assigns SPU 3908 to process a network spulet. Anetwork spulet comprises a program for processing the network protocolof network 104. In this case, this protocol is the Transmission ControlProtocol/Internet Protocol (TCP/IP). TCP/IP data packets conforming tothis protocol are transmitted over network 104. Upon receipt, SPU 3908processes these packets and assembles the data in the packets intosoftware cells 102. In step 4012, PU 3904 instructs SPU 3908 to performresident terminations upon the completion of the processing of thenetwork spulet. In step 4014, PU 3904 assigns PUs 3910 and 3912 toprocess MPEG spulets. In step 4015, PU 3904 instructs SPUs 3910 and 3912also to perform resident terminations upon the completion of theprocessing of the MPEG spulets. In step 4016, PU 3904 designates sandbox3920 as a source sandbox for access by SPU 3908 and SPU 3910. In step4018, PU 3904 designates sandbox 3922 as a destination sandbox foraccess by SPU 3910. In step 4020, PU 3904 designates sandbox 3924 as asource sandbox for access by SPU 3908 and SPU 3912. In step 4022, PU3904 designates sandbox 3926 as a destination sandbox for access by SPU3912. In step 4024, SPU 3910 and SPU 3912 send synchronize read commandsto blocks of memory within, respectively, source sandbox 3920 and sourcesandbox 3924 to set these blocks of memory into the blocking state. Theprocess finally moves to step 4028 where establishment of the dedicatedpipeline is complete and the resources dedicated to the pipeline arereserved. SPUs 3908, 3910 and 3912 and their associated sandboxes 3920,3922, 3924 and 3926, therefore, enter the reserved state.

FIG. 40B illustrates the steps for processing streaming MPEG data bythis dedicated pipeline. In step 4030, SPU 3908, which processes thenetwork spulet, receives in its local storage TCP/IP data packets fromnetwork 104. In step 4032, SPU 3908 processes these TCP/IP data packetsand assembles the data within these packets into software cells 102. Instep 4034, SPU 3908 examines header 3720 (FIG. 37) of the software cellsto determine whether the cells contain MPEG data. If a cell does notcontain MPEG data, then, in step 4036, SPU 3908 transmits the cell to ageneral purpose sandbox designated within DRAM 3918 for processing otherdata by other SPUs not included within the dedicated pipeline. SPU 3908also notifies PU 3904 of this transmission.

On the other hand, if a software cell contains MPEG data, then, in step4038, SPU 3908 examines previous cell ID 3730 (FIG. 37) of the cell toidentify the MPEG data stream to which the cell belongs. In step 4040,SPU 3908 chooses an SPU of the dedicated pipeline for processing of thecell. In this case, SPU 3908 chooses SPU 3910 to process these data.This choice is based upon previous cell ID 3730 and load balancingfactors. For example, if previous cell ID 3730 indicates that theprevious software cell of the MPEG data stream to which the softwarecell belongs was sent to SPU 3910 for processing, then the presentsoftware cell normally also will be sent to SPU 3910 for processing. Instep 4042, SPU 3908 issues a synchronize write command to write the MPEGdata to sandbox 3920. Since this sandbox previously was set to theblocking state, the MPEG data, in step 4044, automatically is read fromsandbox 3920 to the local storage of SPU 3910. In step 4046, SPU 3910processes the MPEG data in its local storage to generate video data. Instep 4048, SPU 3910 writes the video data to sandbox 3922. In step 4050,SPU 3910 issues a synchronize read command to sandbox 3920 to preparethis sandbox to receive additional MPEG data. In step 4052, SPU 3910processes a resident termination. This processing causes this SPU toenter the reserved state during which the SPU waits to processadditional MPEG data in the MPEG data stream.

Other dedicated structures can be established among a group of SPUs andtheir associated sandboxes for processing other types of data. Forexample, as shown in FIG. 41, a dedicated group of SPUs, e.g., SPUs4102, 4108 and 4114, can be established for performing geometrictransformations upon three dimensional objects to generate twodimensional display lists. These two dimensional display lists can befurther processed (rendered) by other SPUs to generate pixel data. Toperform this processing, sandboxes are dedicated to SPUs 4102, 4108 and4114 for storing the three dimensional objects and the display listsresulting from the processing of these objects. For example, sourcesandboxes 4104, 4110 and 4116 are dedicated to storing the threedimensional objects processed by, respectively, SPU 4102, SPU 4108 andSPU 4114. In a similar manner, destination sandboxes 4106, 4112 and 4118are dedicated to storing the display lists resulting from the processingof these three dimensional objects by, respectively, SPU 4102, SPU 4108and SPU 4114.

Coordinating SPU 4120 is dedicated to receiving in its local storage thedisplay lists from destination sandboxes 4106, 4112 and 4118. SPU 4120arbitrates among these display lists and sends them to other SPUs forthe rendering of pixel data.

The processors of system 101 also employ an absolute timer. The absolutetimer provides a clock signal to the SPUs and other elements of a PUwhich is both independent of, and faster than, the clock signal drivingthese elements. The use of this absolute timer is illustrated in FIG.42.

As shown in this figure, the absolute timer establishes a time budgetfor the performance of tasks by the SPUs. This time budget provides atime for completing these tasks which is longer than that necessary forthe SPUs' processing of the tasks. As a result, for each task, there is,within the time budget, a busy period and a standby period. All spuletsare written for processing on the basis of this time budget regardlessof the SPUs' actual processing time or speed.

For example, for a particular SPU of a PU, a particular task may beperformed during busy period 4202 of time budget 4204. Since busy period4202 is less than time budget 4204, a standby period 4206 occurs duringthe time budget. During this standby period, the SPU goes into a sleepmode during which less power is consumed by the SPU.

The results of processing a task are not expected by other SPUs, orother elements of a PU, until a time budget 4204 expires. Using the timebudget established by the absolute timer, therefore, the results of theSPUs' processing always are coordinated regardless of the SPUs' actualprocessing speeds.

In the future, the speed of processing by the SPUs will become faster.The time budget established by the absolute timer, however, will remainthe same. For example, as shown in FIG. 42, an SPU in the future willexecute a task in a shorter period and, therefore, will have a longerstandby period. Busy period 4208, therefore, is shorter than busy period4202, and standby period 4210 is longer than standby period 4206.However, since programs are written for processing on the basis of thesame time budget established by the absolute timer, coordination of theresults of processing among the SPUs is maintained. As a result, fasterSPUs can process programs written for slower SPUs without causingconflicts in the times at which the results of this processing areexpected.

In lieu of an absolute timer to establish coordination among the SPUs,the PU, or one or more designated SPUs, can analyze the particularinstructions or microcode being executed by an SPU in processing anspulet for problems in the coordination of the SPUs' parallel processingcreated by enhanced or different operating speeds. “No operation”(“NOOP”) instructions can be inserted into the instructions and executedby some of the SPUs to maintain the proper sequential completion ofprocessing by the SPUs expected by the spulet. By inserting these NOOPsinto the instructions, the correct timing for the SPUs' execution of allinstructions can be maintained.

FIG. 43 is a flowchart showing the steps taken to compile a given sourcecode into object files adapted to execute in a heterogeneous processorenvironment. Processing commences at 4300 whereupon, at step 4305, arequest is received from a programmer or automated process to compilesource code. The request may include compiler options 4310. Theprogrammer or automated process can set compiler options to determinewhether the source code is compiled into object code adapted to beexecuted on an SPU processor, a PU processor, or both.

At step 4315, source code 4320 is read. A determination is made, basedon the compiler options, as to whether source code 4320 is to becompiled for multiple processors (decision 4325). If the source code isbeing compiled for multiple processors, decision 4325 branches to “yes”branch 4328 to analyze the code and create two object files—one adaptedto run on one or more SPU processors and another object file adapted torun on one or more PU processors.

The data locality is analyzed in step 4330 and a value is assigned basedon the analysis. SPU processors are generally better at handlingstreaming data, while PU processors are generally better at handlingscattered data (scattered data being where subsequent blocks of data forprocessing are found in discontiguous memory locations while instreaming data, the data being processed is generally contiguous. In oneembodiment, the programmer inserts compiler flags or other indicators inthe source code indicating that various portions of the source code areprocessing streaming or scattered data. If the data processing of thesource code is found to be more streaming in nature a higher value isassigned than if the data processing is found to be scattered.

The computational needs of the source program are analyzed at step 4335and a value is assigned based on the analysis. SPU processors aregenerally better at handling more computationally intensive tasks,especially mathematical tasks, than the PU processors. If thecomputational intensity of the program is found to be high, then ahigher value is assigned. Likewise, if the computational intensity islow, a lower value is assigned.

At step 4340, the data parallelism of the data being processed by thesource code is analyzed and a value is assigned based on the analysis.SPU processors are generally better at processing parallel sets of dataas, in one embodiment, the SPU processors are SIMD (Single InstructionMultiple Data) processors able to perform a single instruction againstmore than one set of data. Parallel streams of data can be read into theSPU processors memory and processed simultaneously using the sameinstructions. However, in a non-SIMD processor, such as a traditional PUprocessor, each stream of data is processed separately with the sameinstructions used multiple times to process the multiple streams ofdata. If the data parallelism is found to be high, then a higher valueis assigned. Likewise, if the data parallelism is found to be low, thena lower value is assigned.

At step 4345, the source code is compiled into PU object 4350 that isadapted to be loaded and executed on the PU (i.e., PU machineinstructions suitable for the PU environment). The compiled objectincludes a header area that contains the values from the analysesperformed in steps 4330-4340. These values will subsequently be used bywhen the program is invoked to determine whether to load the PU objector the SPU object.

At step 4355, the source code is compiled into SPU object 4360 that isadapted to be loaded and executed on the SPU (i.e., SPU machineinstructions suitable for the SPU environment). The compiled objectincludes a header area that contains the values from the analysesperformed in steps 4330-4340. These values will subsequently be used bywhen the program is invoked to determine whether to load the PU objector the SPU object. Compilation processing thereafter ends at 4395.

Returning to decision 4325, if the software code is not being compiledfor multiple processors, decision 4325 branches to “no” branch 4368whereupon a determination is made as to whether the source code is beingcompiled for the PU environment or the SPU environment (decision 4370).If the source code is only being compiled for the PU environment,decision 4370 branches to “PU” branch 4372 whereupon, at step 4375, thecode is compiled into PU object 4380 suitable for executing in the PUenvironment. Similarly, if the source code is being compiled for the SPUenvironment, decision 4370 branches to “SPU” branch 4372 whereupon, atstep 4385, the code is compiled into SPU object 4390 suitable forexecuting in the SPU environment. Compilation processing thereafter endsat 4395.

FIG. 44 is a flowchart showing steps taken by a loader in theheterogeneous processor environment selecting in selecting one of theheterogeneous processor types to execute an object file. Processingcommences at 4400 whereupon, at step 4402, a load request is received toload and execute an executable program (i.e., an object file).

At step 4405, object file(s) 4410 and data 4415 matching the request areretrieved. The object file(s) are retrieved from a nonvolatile storagedevice, while the data is either retrieved from a nonvolatile storagedevice or from a memory location if the data was generated from anotherprocess.

A determination is made as to whether there is a single object file(i.e., the program is only suitable for one of the processingenvironments) or more than one object file matching the request(decision 4420). If there are more than one object file matching therequest, decision 4420 branches to “no” branch 4422 whereupon theprocessor to be used for executing one of the objects is identified(predefined process 4425, see FIG. 45 and corresponding text forprocessing details). On the other hand, if there is only one processingenvironment, decision 4420 branches to “yes” branch 4428 bypassingpredefined process 4425.

A determination is made as to whether to execute on the PU or SPUprocessing environment based upon whether there is only a single objectand, if multiple objects are available, which environment is preferredbased upon program characteristics and current processor availability(decision 4430). If the PU processor was selected, decision 4430branches to “PU” branch 4432 whereupon, at step 4435, the PU object codeis loaded into common (shared) memory 4470. If the data being processeddoes not yet reside in memory 4470, it is also loaded (i.e., retrievedfrom nonvolatile storage) into memory 4470. At step 4440, an outputbuffer is initialized. The output buffer is used to store data resultingfrom the execution of the PU object. It can be initialized by the loaderor can be allocated later through instructions included in the PUobject. At step 4445, the PU object is scheduled for execution on one ofthe PU processors by writing the PU object's identifier into run queue4450. The PU's scheduler (4455) dispatches tasks, including the newlyscheduled PU object, for execution by PU processor 4460. Load processingthereafter ends at 4495.

Returning to decision 4430, if the SPU processor environment wasselected, decision 4430 branches to “SPU” branch 4462 whereupon, at step4465, the SPU object is loaded into common (shared) memory 4470. If thedata being processed does not yet reside in memory 4470, it is alsoloaded into memory 4470. At step 4468, an output buffer is initializedin memory 4470. The output buffer is the location to which the SPU willwrite, via a DMA command, data resulting from the SPU's execution of theSPU object. At step 4475, an instruction block is created and written tocommon memory 4470. The instruction block details the address of the SPUobject file that was loaded into common memory 4470, the address of theinput buffer located in common memory that the SPU will process, theaddress of the output buffer, also stored in common memory 4470, towhich the SPU will write data resulting from the SPU's processing of theSPU object file. The instruction block can also include other parametersthat are being passed to the SPU object, such as write-back addressesand parameters particular to the object being executed. At step 4480,the address of the instruction block is written to a mailbox (4485)corresponding to one of the SPUs (for a detailed description of theSPU's execution of the object file, see FIG. 46). Load processingthereafter ends at 4495.

FIG. 45 is a flowchart showing steps taken by the loader in theheterogeneous processor environment identifying a preferred processorfor a given task. Processing commences at 4500 when this routine wascalled from predefined process 4425 shown in FIG. 44. Returning to FIG.45, upon commencing, at step 4505, processor availability is retrieved.If availability of the PU processor (or processors) is greater (better)than SPU availability, then a low value is assigned. Likewise, ifavailability of the SPU processors is greater (better) than availabilityof the PU processor (or processors), then a high value is assigned. Ifboth processor types are equally available, then a middle (neutral)value is assigned.

A determination is made, based on the analysis of processor availabilityin step 4505, as to whether one of the processor types is currentlyunavailable (decision 4510). If one of the processor types (PU or SPU)is currently unavailable, decision 4510 branches to “yes” branch 4570whereupon a determination is made as to whether to wait for theunavailable processor type to become available (decision 4575). If it isdecided to wait for the unavailable processor type to become available,decision 4575 branches to “yes” branch 4580 whereupon, at step 4580,processing waits until the unavailable processor type is available and,when the processor type is available, processing branches to step 4520,described below. On the other hand, if it is decided not to wait for theunavailable processor type to become available, decision 4575 branchesto “no” branch 4585 whereupon, at step 4590, the task is assigned towhichever processor type is available. Processing then returns at 4595(see FIG. 44).

Returning to decision 4510, if both processor types are currentlyavailable, decision 4510 branches to “no” branch 4515 whereupon, at step4520-4530, characteristics of the object being loaded are retrieved froma header area associated with the object. Data in the header area waswritten to the header area during compilation (see FIG. 43 forcompilation details).

At step 4520, the computational intensity value is retrieved from theobject's header area. A high computational intensity value indicatesthat the task is generally more suited to being run on an SPU processor,whereas a lower computational intensity value indicates that thecomputations can be performed well on the PU processor.

At step 4525, the data locality value is retrieved from the object'sheader area. A high data locality value indicates that the data islocalized (i.e., more streamed than scattered). Streamed data isgenerally processed more efficiently by the SPU processor, whilescattered data is generally processed more efficiently by the PUprocessor.

At step 4530, the data parallelism value is retrieved from the object'sheader area. A high data parallelism value indicates that the data canbe processed by the SIMD (Single-Instruction-Multiple-Data) operationsavailable on the SPU. A low data parallelism value indicates that thedata is not highly parallelized and will not be able to utilize the SIMDaspects of the SPU processor, so the PU processor can be utilizedinstead of the SPU processor.

At step 4535, the size of the data being processed is identified bychecking the size of the input buffer or data file that will beprocessed by the object. SPUs are generally better than the PU processorat processing large quantities of data quickly. Therefore, a largerinput data file being processed is given a higher data size score thansmaller input files.

At step 4538, an overall score is computed by combining the processoravailability score, the computational intensity score, the data localityscore, the data parallelism score, and the data size score. In oneembodiment the scores are simply added together. For example, each scoremay be worth a maximum of ten so, by combining the five scores, amaximum value of 50 is available as an overall score. In otherembodiments, the scores are weighted based on the particular function ofthe computer system or after tuning the system with regards to commontasks that are performed. In any event, an overall score is achievedthat is used to determine whether to assign the task to the PU or theSPU.

A determination is made, based on the overall score, as to whether theoverall score is high-or low (decision 4540). Using a simple model, ifthe maximum possible overall score is 50, then a score greater than 25could be considered high. The “high” value can also be tuned to assignmore, or less, tasks to the SPU. For example, after tuning, a “high”score may be set at 20 to assign more tasks to the SPU or may be set at30 to assign more tasks to the PU. If the overall score is high,decision 4540 branches to “yes” branch 4545 whereupon the task isassigned to be performed by an SPU, at step 4550, and at step 4555 oneor more SPUs are identified based upon the SPUs' current availability.On the other hand, if the overall score is not high, decision 4540branches to “no” branch 4560 whereupon the task is assigned to a PU (seeFIG. 44 for details on the loader adding the task to the PU's run queue,and see FIGS. 44 and 46 for details on the loader instructing a SPU toperform the task (FIG. 44) and the SPU retrieving and performing thetask (FIG. 46).

FIG. 46 is a flowchart showing steps taken by an SPU processor inexecuting an object file scheduled to it by the loader. FIG. 44 showedthe steps of the loader creating instruction blocks 4635 (seeinstruction block stored to common memory 4470 in FIG. 44) and notifyingthe SPU by signaling SPU mailbox 4615 (see 4485 in FIG. 44). Processingcommences at 4600 whereupon, at step 4610, the SPU checks mailbox 4615.A determination is made as to whether the mailbox is empty or hasentries to process (decision 4620). If the mailbox is empty, decision4620 branches to “yes” branch 4622 which continues to check the mailbox.In one embodiment, the SPU is interrupted when an entry arrives in themailbox and when there are no entries in the mailbox (and the SPU is notbusy processing a task), the SPU enters a low power state while it waitsfor an entry to arrive.

When an entry arrives, decision 4620 branches to “no” branch 4628whereupon, at step 4630, the address in the mailbox is retrieved andused to retrieve instruction block 4635 stored in the common (shared)memory. The SPU retrieves the instruction block using a DMA command. Inone embodiment, a DMA controller is provided for each SPU and PU toperform DMA commands and retrieve and store data to the common, sharedmemory. The instruction block includes a code address for the code thatthe SPU is to execute, an input buffer address for the input buffer ofthe data that is to be processed, an output buffer address for theoutput buffer where data resulting from the SPU's execution of the codeis to be stored, and an optional signal instruction, such as awrite-back address, that the SPU should use to indicate when it isfinished processing the data. In addition, other parameters that mightbe used by the code can be included in the instruction block andprovided as input to the code once it has been loaded by the SPU.

At step 4640, the code referenced in the instruction block is moved,using a DMA command, from shared memory location 4680 in shared (common)memory 4675 to the SPU's local memory (4695). In one embodiment, the SPUlocal storage is 128K bytes in length.

At step 4650, the code that has been loaded is execute. Prior to andduring execution, blocks from input buffer 4685 located in shared(common) memory 4675 are written to the SPU's local memory 4695 usingDMA commands. The amount of data that can be read into the SPU's localmemory depends on the size of the code being executed and the amount oflocal memory that is reserved for storing result data. During execution,blocks from SPU local memory 4695 that contain results from executingthe code are written to output buffer 4690 located in shared (common)memory 4675 using DMA commands. Again, the amount of SPU local memorythat can be used to store result data before the data needs to bewritten back to the shared memory depends upon the size of the codebeing executed and the amount of space reserved to store input data.

At step 4660, execution of the code ends and the last results fromprocessing the code have been written from SPU local memory back to theshared memory using a DMA command. The SPU, at step 4670, notifies thescheduler (loader) that it is finished executing the code. At thispoint, the SPU loops back to check its mailbox to determine whetherthere are additional requests to process and, if the mailbox is empty,wait for new requests to arrive.

FIG. 47 is a block diagram illustrating a processing element having amain processor and a plurality of secondary processors sharing a systemmemory. Processor Element (PE) 4705 includes processing unit (PU) 4710,which, in one embodiment, acts as the main processor and runs anoperating system. Processing unit 4710 may be, for example, a Power PCcore executing a Linux operating system. PE 4705 also includes aplurality of synergistic processing complex's (SPCs) such as SPCs 4745,4765, and 4785. The SPCs include synergistic processing units (SPUs)that act as secondary processing units to PU 4710, a memory storageunit, and local storage. For example, SPC 4745 includes SPU 4760, MMU4755, and local storage 4759; SPC 4765 includes SPU 4770, MMU 4775, andlocal storage 4779; and SPC 4785 includes SPU 4790, MMU 4795, and localstorage 4799.

Each SPC may be configured to perform a different task, and accordingly,in one embodiment, each SPC may be accessed using different instructionsets. If PE 4705 is being used in a wireless communications system, forexample, each SPC may be responsible for separate processing tasks, suchas modulation, chip rate processing, encoding, network interfacing, etc.In another embodiment, the SPCs may have identical instruction sets andmay be used in parallel with each other to perform operations benefitingfrom parallel processing.

PE 4705 may also include level 2 cache, such as L2 cache 4715, for theuse of PU 4710. In addition, PE 4705 includes system memory 4720, whichis shared between PU 4710 and the SPUs. System memory 4720 may store,for example, an image of the running operating system (which may includethe kernel), device drivers, I/O configuration, etc., executingapplications, as well as other data. System memory 4720 includes thelocal storage units of one or more of the SPCs, which are mapped to aregion of system memory 4720. For example, local storage 4759 may bemapped to mapped region 4735, local storage 4779 may be mapped to mappedregion 4740, and local storage 4799 may be mapped to mapped region 4742.PU 4710 and the SPCs communicate with each other and system memory 4720through bus 4717 that is configured to pass data between these devices.

The MMUs are responsible for transferring data between an SPU's localstore and the system memory. In one embodiment, an MMU includes a directmemory access (DMA) controller configured to perform this function. PU4710 may program the MMUs to control which memory regions are availableto each of the MMUs. By changing the mapping available to each of theMMUs, the PU may control which SPU has access to which region of systemmemory 4720. In this manner, the PU may, for example, designate regionsof the system memory as private for the exclusive use of a particularSPU. In one embodiment, the SPUs' local stores may be accessed by PU4710 as well as by the other SPUs using the memory map. In oneembodiment, PU 4710 manages the memory map for the common system memory4720 for all the SPUs. The memory map table may include PU 4710's L2Cache 4715, system memory 4720, as well as the SPUs' shared localstores.

In one embodiment, the SPUs process data under the control of PU 4710.The SPUs may be, for example, digital signal processing cores,microprocessor cores, micro controller cores, etc., or a combination ofthe above cores. Each one of the local stores is a storage areaassociated with a particular SPU. In one embodiment, each SPU canconfigure its local store as a private storage area, a shared storagearea, or an SPU may configure its local store as a partly private andpartly shared storage.

For example, if an SPU requires a substantial amount of local memory,the SPU may allocate 100% of its local store to private memoryaccessible only by that SPU. If, on the other hand, an SPU requires aminimal amount of local memory, the SPU may allocate 10% of its localstore to private memory and the remaining 90% to shared memory. Theshared memory is accessible by PU 4710 and by the other SPUs. An SPU mayreserve part of its local store in order for the SPU to have fast,guaranteed memory access when performing tasks that require such fastaccess. The SPU may also reserve some of its local store as private whenprocessing sensitive data, as is the case, for example, when the SPU isperforming encryption/decryption.

Although the invention herein has been described with reference toparticular embodiments, it is to be understood that these embodimentsare merely illustrative of the principles and applications of thepresent invention. It is therefore to be understood that numerousmodifications may be made to the illustrative embodiments and that otherarrangements may be devised without departing from the spirit and scopeof the present invention as defined by the appended claims.

One of the preferred implementations of the invention is an application,namely, a set of instructions (program code) in a code module which may,for example, be resident in the random access memory of the computer.Until required by the computer, the set of instructions may be stored inanother computer memory, for example, on a hard disk drive, or inremovable storage such as an optical disk (for eventual use in a CD ROM)or floppy disk (for eventual use in a floppy disk drive), or downloadedvia the Internet or other computer network. Thus, the present inventionmay be implemented as a computer program product for use in a computer.In addition, although the various methods described are convenientlyimplemented in a general purpose computer selectively activated orreconfigured by software, one of ordinary skill in the art would alsorecognize that such methods may be carried out in hardware, in firmware,or in more specialized apparatus constructed to perform the requiredmethod steps.

While particular embodiments of the present invention have been shownand described, it will be obvious to those skilled in the art that,based upon the teachings herein, changes and modifications may be madewithout departing from this invention and its broader aspects and,therefore, the appended claims are to encompass within their scope allsuch changes and modifications as are within the true spirit and scopeof this invention. Furthermore, it is to be understood that theinvention is solely defined by the appended claims. It will beunderstood by those with skill in the art that if a specific number ofan introduced claim element is intended, such intent will be explicitlyrecited in the claim, and in the absence of such recitation no suchlimitation is present. For a non-limiting example, as an aid tounderstanding, the following appended claims contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimelements. However, the use of such phrases should not be construed toimply that the introduction of a claim element by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim element to inventions containing only one such element,even when the same claim includes the introductory phrases “one or more”or “at least one” and indefinite articles such as “a” or “an”; the sameholds true for the use in the claims of definite articles.

1. A computer-implemented method to load objects in a heterogeneous multiprocessor computer system, said method comprising: analyzing a source program for one or more program characteristics, the program characteristics selected from the group consisting of data locality, computational intensity, and data parallelism; in response to the analyzing, compiling the source program into two object files, a first object file corresponding to a first instruction set and a second object file corresponding to a second instruction set; in response to the compiling, storing the program characteristics in each of the object files; receiving a request to execute a software task corresponding to the source program; selecting a processor from a plurality of dislike processors, wherein a first processor corresponds to the first instruction set and a second processor corresponds to the second instruction set, to execute the software task, the selecting comprising comparing one or more characteristics of the software task with the program characteristics stored in the first object file and the second object file; in response to selecting the first processor: loading the first object file into a shared memory, wherein the shared memory is shared by the plurality of dislike processors; and executing the loaded first object file by the first processor; and in response to selecting the second processor: loading the second object file into the shared memory; and executing the loaded second object file by the second processor.
 2. The method as described in claim 1 wherein selecting the processor further comprises: retrieving the program characteristics; retrieving current system characteristics, wherein the current system characteristics includes processor load characteristics for the plurality of dislike processors; and combining the program characteristics and the current system characteristics to determine which of the dislike processors to assign the software task.
 3. The method as described in claim 2 wherein at least one of the current system characteristics is selected from the group consisting of processor availability for each of the dislike processors, and a data size of data being processed by the software task.
 4. The method as described in claim 1 wherein executing the first object file by the first processor further comprises: determining that the first processor has a scheduler that schedules tasks for the first processor; and scheduling the first object file to execute on the first processor, the scheduling including: writing a software code identifier corresponding to the first object file to a run queue corresponding to the first processor.
 5. The method as described in claim 1 wherein executing the second object file by the second processor further comprises: signaling the second processor; and reading, by the second processor, the second object file from the shared memory into a local memory corresponding to the second processor.
 6. The method as described in claim 5 further comprising: writing an instruction block in the shared memory, the instruction block including an address of the loaded second object file and an address of an input buffer; and reading the loaded second object file and the input buffer from the locations identified in the instruction block to the second processor's local memory.
 7. The method as described in claim 6 further comprising: signaling the second processor from one of the other processors, the signaling including: writing the address of the instruction block to a mailbox that corresponds to the second processor; and reading, by the second processor, the instruction block in response to the signal. 